Assessment of insect occurrence in boreal forests based on satellite imagery and field measurements.

The presence/absence data of twenty-seven forest insect taxa (e.g. Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, S Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models varied between species, possibly because some species may be associated with the characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocoetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

Peeking through the Iron Curtain: Memories of Watching Finnish Television in Estonia during Soviet Occupation

The present study analyses the memories of watching Finnish television in Estonia during the last decades of the Soviet occupation from the late 1960s until the beginning of 1990s. The study stems from a culturalist approach, perceiving television as a relevant aspect in the audiences’ everyday lives. It explores the significance of Finnish television on the society of occupied Estonia from the point of view of its historical audiences. The literature review concentrates on concepts such as the power of television, transnational media, historical audience reception and memory as an object of research. It also explains the concept of spillover, which refers to the unintentional bilateral flow of television signals from one country to another. Despite the numerous efforts of the Soviet authorities to prevent the viewing of the "bourgeois television", there still remained a small gap in the Iron Curtain. The study describes the phenomenon of watching Finnish television in Estonia. It provides understanding about the significance of watching Finnish television in Soviet Estonia through the experiences of its former audience. In addition, it explores what do people remember about watching Finnish television, and why. The empirical data was acquired from peoples’ personal memories through the analysis of private interviews and written responses during the period from February 2010 to February 2011. A total of 85 responses (5 interviews and 83 written responses) were analysed. The research employed the methods of oral history and memory studies. The main theoretical sources of the study include the works of Mati Graf and Heikki Roiko-Jokela, Hagi Šein, Sonia Livingstone, Janet Staiger and Emily Keightley. The study concludes that besides fulfilling the role of an entertainer and an informer, Finnish television enabled its Estonian audiences to gain entry into the imaginary world. Access to this imaginary world was so important, that the viewers engaged in illegal activities and gained special skills, whereby a phenomenon of "television tourism" developed. Most of the memories about Finnish television are vivid and similar. The latter indicates both the reliability and the collectiveness of such memories, which in return give shape to collective identities. Thus, for the Estonian viewers, the experience of watching Finnish television during the Soviet occupation has became part of their identity.

Impact of satellite observed microwave SST on the simulation of tropical cyclones

The impact of realistic representation of sea surface temperature (SST) on the numerical simulation of track and intensity of tropical cyclones formed over the north Indian Ocean is studied using the Weather Research and Forecast (WRF) model. We have selected two intense tropical cyclones formed over the Bay of Bengal for studying the SST impact. Two different sets of SSTs were used in this study: one from TRMM Microwave Imager (TMI) satellite and other is the weekly averaged Reynold's SST analysis from National Center for Environmental Prediction (NCEP). WRF simulations were conducted using the Reynold's and TMI SST as model boundary condition for the two cyclone cases selected. The TMI SST which has a better temporal and spatial resolution showed sharper gradient when compared to the Reynold's SST. The use of TMI SST improved the WRF cyclone intensity prediction when compared to that using Reynold's SST for both the cases studied. The improvements in intensity were mainly due to the improved prediction of surface latent and sensible heat fluxes. The use of TMI SST in place of Reynold's SST improved cyclone track prediction for Orissa super cyclone but slightly degraded track prediction for cyclone Mala. The present modeling study supports the well established notion that the horizontal SST gradient is one of the major driving forces for the intensification and movement of tropical cyclones over the Indian Ocean.

Multi-spectral satellite image classification using Glowworm Swarm Optimization

This paper investigates a new Glowworm Swarm Optimization (GSO) clustering algorithm for hierarchical splitting and merging of automatic multi-spectral satellite image classification (land cover mapping problem). Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to classify all the basic land cover classes of an urban region in a satisfactory manner. In unsupervised classification methods, the automatic generation of clusters to classify a huge database is not exploited to their full potential. The proposed methodology searches for the best possible number of clusters and its center using Glowworm Swarm Optimization (GSO). Using these clusters, we classify by merging based on parametric method (k-means technique). The performance of the proposed unsupervised classification technique is evaluated for Landsat 7 thematic mapper image. Results are evaluated in terms of the classification efficiency - individual, average and overall.